代码搜索：classification
找到约 3,679 项符合「classification」的源代码
代码结果 3,679
www.eeworm.com/read/317668/13500033
classification_activex2
www.eeworm.com/read/317622/13500818
m classification_error.m
function [classify, err] = classification_error(D, patterns, targets, region)
%Find a classification error for a given decision surface D and a given set of
%patterns (2xL) and targets (1xL)
%The
www.eeworm.com/read/316604/13520395
m classification_error.m
function [classify, err] = classification_error(D, features, targets, region)
%Find a classification error for a given decision surface D and a given set of
%features (2xL) and targets (1xL)
%The
www.eeworm.com/read/315311/13546584
html keysym-classification.html
Xlib Programming Manual: KeySym Classification Macros
16.1.1 KeySym Classification Macros
You may want to test if a KeySym is, for e
www.eeworm.com/read/359185/6352484
m classification_error.m
function [classify, err] = classification_error(D, features, targets, region)
%Find a classification error for a given decision surface D and a given set of
%features (2xL) and targets (1xL)
%The
www.eeworm.com/read/493206/6398462
m classification_error.m
function [classify, err] = classification_error(D, features, targets, region)
%Find a classification error for a given decision surface D and a given set of
%features (2xL) and targets (1xL)
%The
www.eeworm.com/read/489510/6471968
txt classification2.txt
%prony法模态参数识别
%%%%%%%%%%%%%%%%%%%%%
%clear
clc
close all hidden
format long
%%%%%%%%%%%%%%%%%%%%%%%%%%%
fni=input('prony模式识别数据文件名:','s');
%fni=out2.signals.values, 'DisplayName', 'out2.signals
www.eeworm.com/read/410924/11264772
m classification_error.m
function [classify, err] = classification_error(D, features, targets, region)
%Find a classification error for a given decision surface D and a given set of
%features (2xL) and targets (1xL)
%The
www.eeworm.com/read/405126/11471110
pdf 3classification.pdf
www.eeworm.com/read/405069/11472166
m classification_error.m
function [classify, err] = classification_error(D, patterns, targets, region)
%Find a classification error for a given decision surface D and a given set of
%patterns (2xL) and targets (1xL)
%The